Applied Audio Machine Learning Engineer

About the position

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. Google's Extended Reality (XR) team is developing Augmented Reality (AR) and Virtual Reality (VR) technologies that integrate digital information into the physical world. Our mission is to empower devices like headsets and glasses to understand and interact with the environment from the user's perspective. The Extended Reality (XR) Audio Machine Learning team focuses on creating machine learning models to improve audio experiences in XR devices, including speech denoising, separation, conversation detection, and spatial audio. The role address challenges like detecting speech in noisy environments and sub-vocal speech detection. In this role, you will design and optimize Machine Learning models for voice interfaces in wearable devices, ensuring real-time audio processing to understand users in dynamic environments and contribute to the future of Augmented Reality and Virtual Reality technology. The Google Augmented Reality team is a group of experts tasked with building the foundations for great immersive computing and building helpful, delightful user experiences. We're focused on making immersive computing accessible to billions of people through mobile devices, and our scope continues to grow and evolve.

Responsibilities

• Develop and optimize machine learning models for audio processing, including speech denoising, separation, and conversation detection, ensuring high performance and low latency in XR devices.
• Collaborate with cross-functional teams, including hardware engineers, product managers, and designers, to ensure seamless integration of ML models into wearable XR devices and systems, focusing on best practices in code quality, performance, and testability.
• Contribute and maintain technical documentation, providing clear insights into model development, updates, and optimizations based on feedback from product teams and real-world usage.
• Identify, troubleshoot, and resolve issues related to model performance, analyzing the interaction between hardware, software, and network conditions to optimize audio processing on devices.
• Design and implement GenAI solutions, leveraging ML infrastructure to improve model accuracy, optimize for real-time deployment, and enhance data processing workflows for robust audio performance in XR applications.

Requirements

• Bachelor's degree or equivalent practical experience.
• 2 years of experience with data structures or algorithms.
• 2 years of experience with software development in Python, C++, or Java, or 1 year of experience with an advanced degree.
• 1 year of experience developing and deploying machine learning models for audio, including speech processing (e.g., denoising, separation) or generative AI in multi-modal applications (e.g., text, image, video, audio).
• 1 year of experience with ML systems, including data preprocessing, model training, evaluation for real-time applications on mobile/embedded platforms (e.g., Android), with a focus on audio processing and production performance.

Nice-to-haves

• Master's degree or PhD in Computer Science or related technical fields.
• Experience in machine learning principles and model architectures.
• Experience in model development, including training and optimization.
• Experience in developing accessible technologies.

Benefits

• 401k
• health_insurance
• dental_insurance
• vision_insurance
• life_insurance
• disability_insurance
• paid_holidays
• paid_volunteer_time
• tuition_reimbursement
• professional_development
• employee_stock_purchase_plan
• performance_bonus
• sign_on_bonus
• flexible_scheduling